Doctoral Research

Doctoral Research

PhD studentship 

We are seeking a PhD student (3 year, UK fees + stipend; start date 1 Oct 2018) to join our team of researchers working on the SpInspired research project funded by EPSRC and the University of York, UK.  SpInspired is developing a methodology for exploiting unconventional computing in unconventional materials such as carbon nanotubes, NMR, and liquid crystals.  It is an interdisciplinary collaboration between researchers from York’s Departments of Computer Science, Electronic Engineering, and Chemistry, and the York Cross-disciplinary Centre for Systems Analysis (YCCSA).

As we approach the miniaturisation limits of conventional electronics, alternatives to silicon transistors -- the building blocks of the multitude of today’s electronic devices -- are being hotly pursued.  Unconventional computing exploits unconventional material substrates within which to perform computation. Practical unconventional computing devices can comprise multiple unconventional substrates, each performing the part of the overall computation that it does best. For example, a bacterial system may be combined with an optical system to solve the `wiring problem' of composing components, or a reaction-diffusion chemical system may be combined with a microfluidic droplet system to provide a range of contexts for the reactions. In even the simplest cases, an unconventional substrate is often combined with a conventional digital computer, for example carbon nanotubes in an evolutionary algorithm loop controlled by a traditional PC.

We have developed a computational framework called Heterotic computing (named from the term in genetics meaning ‘hybrid vigour’), which can be used to extend a theory of unconventional computing to such multiple substrates.

Heterotic Computing: Practice

Department of Electronic Engineering; YCCSA

The goal of this PhD research is to develop the practice of heterotic computing, in order to provide a practical means for designing, constructing, evaluating, and exploiting future heterotic computers. Instead of creating computing devices from predefined discrete components, the physical properties of electrically active random disordered materials in combination with suitable electronic configuration will be utilised to perform computation with them.

This project is focussed on one of the most challenging research questions in heterotic computing, which is the choice and evaluation of materials that exhibit the desired properties and behaviours to make them good computers.This will include the preparation and application of nano materials as computational substrates, initially looking at a combination of carbon nanotubes, graphene and liquid crystal. Guided by the initial results other unconventional materials will be included.

The project would suit a student with any science and/or engineering background with a keen interest in interdisciplinary work between environment, biology and computing/engineering. Basic knowledge of electronics and programming would be beneficial.

This PhD research will be co-supervised by
Dr Martin Trefzer (Dept Electronic Engineering; YCCSA) martin.trefzer@york.ac.uk
Dr Simon O’Keefe (Dept Computer Science; YCCSA) simon.okeefe@york.ac.uk


Using machine learning to predict cell type and fate in heterogeneous populations

Department of Chemistry

This interdisciplinary project will use label-free ptychographic imaging to visualise behaviour of cells over time in heterogeneous cultures. Mixed neuronal cultures will be used to interrogate the behaviour of microglia, the resident immune cell population in the brain. Cells will be tracked over time to generate trajectories with information on distance travelled, velocity, changes in morphology, as well as unique metrics such as mass, granularity, cell volume. The student will use pattern recognition and machine learning algorithms to characterize particle movements with features extracted from the time-series. The local environment (e.g. density and dispersion of neighbouring cells) will be analysed and changes in behaviour related to any environmental differences. The aim is to identify a minimal set of measurements that can determine particular behaviour patterns and facilitate the identification of specific cell types within the heterogeneous population. Cell identity will be confirmed using established approaches, including immunocytochemistry and flow cytometry. The models developed, together with pharmacological and genetic approaches, will be used to explore basic biological mechanisms that regulate the behaviour of a relatively understudied cell type (microglia) that plays a critical function in the normal brain and in several disease states.

The project crosses disciplinary boundaries and could suit a computer science or mathematics graduate with a strong interest in biology or a computational biologist. The project will provide the student with key skills and exposure to new, cutting-edge technologies as well as applying established techniques to new problems.

BBSRC National Productivity Investment Fund (NPIF) 

For further information, any interested students can contact supervisors for the project: 
Dr Julie Wilson (Maths, YCCSA) julie.wilson@york.ac.uk
Dr Will Brackenbury (Biology), william.brackenbury@york.ac.uk
Dr Peter O'Toole (Technology Facility) peter.otoole@york.ac.uk


If you are thinking of a PhD in YCCSA, you can informally contact any members of staff who you might be interested as a supervior.  They will be able to disucss potential reserarch projects with you prior to any formal applilcation.

All YCCSA PhD students are registered with the relevant Department in the University.  

See IGGI, Intelligent Games and Game Intelligence - EPSRC Centre for Doctoral Training


Take a look at the various Departmental websites for further information

Department of Biology Department of Chemistry
Department of Computer Science Department of Electronics
Enivroment Department - (Stockholm Environment Institute)  Department of Mathematics
The York Management School  











Postdoctoral Research

 Postdoctoral Research

KTP Research Associate in Software Development for the Non-Invasive Detection of Bladder Cancer

Paraytec is a York based scientific instrument company designing, developing and manufacturing the award-winning range of ActiPix ultra violet (UV) area imaging detectors. This project is associated with a new Knowledge Transfer Partnership (KTP) between Paraytec Ltd and the University of York. 
The KTP centres around development of sophisticated image analysis algorithms for detection of bladder cancer cells in urine samples. The successful applicant will lead the research and applied work on this exciting and challenging project and will be able to work collaboratively as part of a multidisciplinary team (from other software and hardware engineers to medical clinicians).

The project is interdisciplinary and applicants with a Masters’ degree or the equivalent experience in computer science, mathematics or other relevant discipline will be considered. Ideally applicants should have:

  • experience in software engineering and design;
  • strong organisational skills and experience in project management;
  • knowledge of instrumentation and data analysis;
  • experience of software/hardware integration, including embedded systems, would be an advantage.

This is a fixed post for 2 years in the first instance with the possibility of further employment.
Salary:  Salary will be fixed at £34,189 per year  
Hours of work:  Full Time (37.5 hours a week)
Based at: Paraytec Ltd, Osbaldwick, York and University of York, Mathematics Department







Potential fellows

Potential Research Fellows

We welcome any applications from potential Fellows with funding who are interested in joining the YCCSA community.

Summer School Scholarships

Summer School Scholarships 

Nine-week summer school scholarships are available within YCCSA. 


Staff vacancies

 Staff vacancies 

There are currently no staff vacancies in YCCSA but please visit Jobs at York